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Zhao J, Zhang Y, Guo D, Zhai J. Ion Gel-Modulated Low-Temperature Field-Effect Phototransistors with Multispectral Responsivity for Artificial Synapses. SENSORS (BASEL, SWITZERLAND) 2025; 25:2750. [PMID: 40363188 PMCID: PMC12074399 DOI: 10.3390/s25092750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2025] [Revised: 04/17/2025] [Accepted: 04/24/2025] [Indexed: 05/15/2025]
Abstract
We report an ion-gel-gated amorphous indium gallium zinc oxide (a-IGZO) optoelectronic neuromorphic transistors capable of synaptic emulation in both photoelectric dual modes. The ion-gel dielectric in the coplanar-structured transistor, fabricated via ink-jet printing, exhibits excellent double-layer capacitance (>1 μF/cm2) and supports low-voltage operation through lateral gate coupling. The integration of ink-jet printing technology enables scalable and large-area fabrication, highlighting its industrial feasibility. Electrical stimulation-induced artificial synaptic behaviors were successfully demonstrated through ion migration in the gel matrix. Through a simple and controllable oxygen vacancy engineering process involving low-temperature oxygen-free growth and post-annealing process, a sufficient density of stable subgap states was generated in IGZO, extending its responsivity spectrum to the visible-red region and enabling wavelength-discriminative photoresponses to 450/532/638 nm visible light. Notably, the subgap states exhibited unique interaction dynamics with low-energy photons in optically triggered pulse responses. Critical synaptic functionalities-including short-term plasticity (STP), long-term plasticity (LTP), and paired-pulse facilitation (PPF)-were successfully simulated under both optical and electrical stimulations. The device achieves low energy consumption while maintaining compatibility with flexible substrates through low-temperature processing (≤150 °C). This study establishes a scalable platform for multimodal neuromorphic systems utilizing printed iontronic architectures.
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Affiliation(s)
- Junjian Zhao
- Beijing Key Laboratory of Micro-Nano Energy and Sensor, Center for High-Entropy Energy and Systems, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China; (J.Z.); (Y.Z.)
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yufei Zhang
- Beijing Key Laboratory of Micro-Nano Energy and Sensor, Center for High-Entropy Energy and Systems, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China; (J.Z.); (Y.Z.)
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Di Guo
- Beijing Key Laboratory of Micro-Nano Energy and Sensor, Center for High-Entropy Energy and Systems, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China; (J.Z.); (Y.Z.)
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Junyi Zhai
- Beijing Key Laboratory of Micro-Nano Energy and Sensor, Center for High-Entropy Energy and Systems, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China; (J.Z.); (Y.Z.)
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
- Center on Nanoenergy Research, School of Physical Science & Technology, Guangxi University, Nanning 530004, China
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Han Y, Seo J, Lee DH, Yoo H. IGZO-Based Electronic Device Application: Advancements in Gas Sensor, Logic Circuit, Biosensor, Neuromorphic Device, and Photodetector Technologies. MICROMACHINES 2025; 16:118. [PMID: 40047564 PMCID: PMC11857157 DOI: 10.3390/mi16020118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/24/2024] [Revised: 01/14/2025] [Accepted: 01/19/2025] [Indexed: 03/09/2025]
Abstract
Metal oxide semiconductors, such as indium gallium zinc oxide (IGZO), have attracted significant attention from researchers in the fields of liquid crystal displays (LCDs) and organic light-emitting diodes (OLEDs) for decades. This interest is driven by their high electron mobility of over ~10 cm2/V·s and excellent transmittance of more than ~80%. Amorphous IGZO (a-IGZO) offers additional advantages, including compatibility with various processes and flexibility making it suitable for applications in flexible and wearable devices. Furthermore, IGZO-based thin-film transistors (TFTs) exhibit high uniformity and high-speed switching behavior, resulting in low power consumption due to their low leakage current. These advantages position IGZO not only as a key material in display technologies but also as a candidate for various next-generation electronic devices. This review paper provides a comprehensive overview of IGZO-based electronics, including applications in gas sensors, biosensors, and photosensors. Additionally, it emphasizes the potential of IGZO for implementing logic gates. Finally, the paper discusses IGZO-based neuromorphic devices and their promise in overcoming the limitations of the conventional von Neumann computing architecture.
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Affiliation(s)
- Youngmin Han
- Department of Semiconductor Engineering, Gachon University, Seongnam 13120, Republic of Korea;
| | - Juhyung Seo
- Department of Electronic Engineering, Gachon University, Seongnam 13120, Republic of Korea
| | - Dong Hyun Lee
- Department of Semiconductor Engineering, Gachon University, Seongnam 13120, Republic of Korea;
| | - Hocheon Yoo
- Department of Semiconductor Engineering, Gachon University, Seongnam 13120, Republic of Korea;
- Department of Electronic Engineering, Gachon University, Seongnam 13120, Republic of Korea
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Yue Y, Yu Z, Li F, Peng W, Zhu Q, He Y. A Low-Cost Flexible Optoelectronic Synapse Based on ZnO Nanowires for Neuromorphic Computing. SENSORS (BASEL, SWITZERLAND) 2024; 24:7788. [PMID: 39686325 DOI: 10.3390/s24237788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2024] [Revised: 12/01/2024] [Accepted: 12/03/2024] [Indexed: 12/18/2024]
Abstract
Neuromorphic computing, inspired by the brain, holds significant promise for advancing artificial intelligence. Artificial optoelectronic synapses, which can convert optical signals into electrical signals, play a crucial role in neuromorphic computing. In this study, we successfully fabricated a flexible artificial optoelectronic synapse device based on the ZnO/PDMS structure by utilizing the magnetron sputtering technique to deposit the ZnO film on a flexible substrate. Under UV light illumination, the device exhibits excellent synaptic plasticity, including excitatory postsynaptic current (EPSC), short-term potentiation (STP), and paired-pulse facilitation (PPF). By growing ZnO nanowires, we improved the fabrication processes and further enhanced the synaptic properties of the device, demonstrating long-term potentiation (LTP) and the transition from short-term memory (STM) to long-term memory (LTM). Additionally, the device exhibits outstanding flexibility, maintaining stable synaptic plasticity under bending conditions. This device shows broad application potential in mimicking visual systems and is expected to contribute significantly to the development of neuromorphic computing.
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Affiliation(s)
- Yongqing Yue
- School of Microelectronics, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Zixia Yu
- School of Microelectronics, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Fangpei Li
- School of Microelectronics, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Wenbo Peng
- School of Microelectronics, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
| | - Quanzhe Zhu
- Shaanxi Advanced Semiconductor Technology Center Co., Ltd., Xi'an 710077, China
| | - Yongning He
- School of Microelectronics, Xi'an Jiaotong University, Xi'an 710049, China
- The Key Lab of Micro-Nano Electronics and System Integration of Xi'an City, Xi'an 710049, China
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He Y, Zhu Y, Wan Q. Oxide Ionic Neuro-Transistors for Bio-inspired Computing. NANOMATERIALS (BASEL, SWITZERLAND) 2024; 14:584. [PMID: 38607119 PMCID: PMC11013937 DOI: 10.3390/nano14070584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 03/24/2024] [Accepted: 03/25/2024] [Indexed: 04/13/2024]
Abstract
Current computing systems rely on Boolean logic and von Neumann architecture, where computing cells are based on high-speed electron-conducting complementary metal-oxide-semiconductor (CMOS) transistors. In contrast, ions play an essential role in biological neural computing. Compared with CMOS units, the synapse/neuron computing speed is much lower, but the human brain performs much better in many tasks such as pattern recognition and decision-making. Recently, ionic dynamics in oxide electrolyte-gated transistors have attracted increasing attention in the field of neuromorphic computing, which is more similar to the computing modality in the biological brain. In this review article, we start with the introduction of some ionic processes in biological brain computing. Then, electrolyte-gated ionic transistors, especially oxide ionic transistors, are briefly introduced. Later, we review the state-of-the-art progress in oxide electrolyte-gated transistors for ionic neuromorphic computing including dynamic synaptic plasticity emulation, spatiotemporal information processing, and artificial sensory neuron function implementation. Finally, we will address the current challenges and offer recommendations along with potential research directions.
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Affiliation(s)
- Yongli He
- Yongjiang Laboratory (Y-LAB), Ningbo 315202, China; (Y.H.); (Y.Z.)
- National Laboratory of Solid-State Microstructures, Collaborative Innovation Center of Advanced Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China
| | - Yixin Zhu
- Yongjiang Laboratory (Y-LAB), Ningbo 315202, China; (Y.H.); (Y.Z.)
- National Laboratory of Solid-State Microstructures, Collaborative Innovation Center of Advanced Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China
| | - Qing Wan
- Yongjiang Laboratory (Y-LAB), Ningbo 315202, China; (Y.H.); (Y.Z.)
- National Laboratory of Solid-State Microstructures, Collaborative Innovation Center of Advanced Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China
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